About the role

We're looking for a Finance Data Scientist to join our central Data team as the first dedicated analytics partner to Finance. You'll turn billing, revenue and forecasting data into audit-ready numbers, and the analysis that shapes pricing and planning decisions as we scale towards IPO.

• Own finance-facing analysis: revenue and ARR reconciliation, cohort and retention economics, pricing and packaging experiments.
• Partner with Analytics Engineering on the certified finance KPI layer (ARR, billing, revenue), and be the first to catch when a number is quietly wrong.
• Build forecasting and scenario models that FP&A uses directly in planning and board reporting.
• Translate ambiguous finance questions from FP&A, RevOps and leadership into clear, reusable analysis.

Requirements

• Demonstrated experience as a data scientist or analyst embedded with a Finance / FP&A function, ideally at a growth-stage or pre-IPO company.
• Strong SQL and Python, with comfort reconciling data across Stripe, Salesforce and a dbt-modelled warehouse.
• Finance fluency: ARR, billing, revenue recognition, cohort economics — you can speak FP&A's language.
• Rigour around data quality: you reconcile by default and can explain a variance, not just report it.
• Strong stakeholder management with Finance leadership, and the ability to push back on ambiguous asks.

Bonus

• Experience preparing finance data for audit, SOX or IPO readiness.
• Experience with pricing / packaging experimentation or revenue forecasting at a subscription or usage-based business.
• Experience with dbt or a modern warehouse (BigQuery), partnering directly with analytics engineers.

Location

This role is remote-first, so it can be executed from anywhere in Europe or the US East Coast, with the ability to operate in CET / ET timezones required. If you prefer, you can work from our offices in London, Warsaw, Dublin or New York.